Genetic variation at hair length candidate genes in elephants and the extinct woolly mammoth
Bibliographic record
Abstract
BACKGROUND: Like humans, the living elephants are unusual among mammals in being sparsely covered with hair. Relative to extant elephants, the extinct woolly mammoth, Mammuthus primigenius, had a dense hair cover and extremely long hair, which likely were adaptations to its subarctic habitat. The fibroblast growth factor 5 (FGF5) gene affects hair length in a diverse set of mammalian species. Mutations in FGF5 lead to recessive long hair phenotypes in mice, dogs, and cats; and the gene has been implicated in hair length variation in rabbits. Thus, FGF5 represents a leading candidate gene for the phenotypic differences in hair length notable between extant elephants and the woolly mammoth. We therefore sequenced the three exons (except for the 3' UTR) and a portion of the promoter of FGF5 from the living elephantid species (Asian, African savanna and African forest elephants) and, using protocols for ancient DNA, from a woolly mammoth. RESULTS: Between the extant elephants and the mammoth, two single base substitutions were observed in FGF5, neither of which alters the amino acid sequence. Modeling of the protein structure suggests that the elephantid proteins fold similarly to the human FGF5 protein. Bioinformatics analyses and DNA sequencing of another locus that has been implicated in hair cover in humans, type I hair keratin pseudogene (KRTHAP1), also yielded negative results. Interestingly, KRTHAP1 is a pseudogene in elephantids as in humans (although fully functional in non-human primates). CONCLUSION: The data suggest that the coding sequence of the FGF5 gene is not the critical determinant of hair length differences among elephantids. The results are discussed in the context of hairlessness among mammals and in terms of the potential impact of large body size, subarctic conditions, and an aquatic ancestor on hair cover in the Proboscidea.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".